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DOE OSTI2025

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗

DOE OSTI2024

Forest structural complexity and ignition pattern influence simulated prescribed fire effects

Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗

DOE OSTI2025

Selective mass scaling for single-layer thick shell elements in DYNA3D

Hexahedral elements can be adapted to model thin and moderately thick structures by neglecting the coupling of through-thickness stress, resulting in a fully three-dimensional, but simplified, state of stress. These specialized elements, often referred to as “thick” or “solid” shells, are generally employed to model thin-walled structures using continuum mechanics-based material models. In explicit dynamics simulations, where computational speed is important, these elements are integrated with a single quadrature point and a set of anti-hourglassing (stabilizing) forces. Thick shells, by definition, have a thickness dimension smaller than their in-plane dimensions, and this small thickness often determines the stable time step size in simulations, despite the mechanics being approximated. To alleviate this limitation while retaining the relevant dynamics of thin-walled structures, selective mass scaling (SMS), or selective mass “augmentation,” has been proposed in the literature. In this technical report, we explore the application of SMS to single-layer thick shells in the simulation software DYNA3D.

42 ENGINEERING↗

DOE OSTI2025

Accelerated Irradiation Testing and Post-Irradiation Characterization: U.S.-Based Capabilities for Advanced Nuclear Systems and Radioisotope Production

Irradiation experiments and post-irradiation examinations, together referred to as irradiation testing (IRT), are prerequisites for nuclear fuel and material qualification for the deployment of new and advanced reactors, as well as radioisotope production, thereby ensuring regulatory compliance. Qualified research and test reactors (RTRs) and testing facilities are essential to enable IRT to verify performance and safety under prototypical reactor conditions. In the past, qualification of new fuels or structural materials required about 20 years. Synergist strategies, advanced tools, and qualified methods are needed to greatly reduce this timeframe of IRT and radioisotope production. This study, termed accelerated-IRT, focuses on identifying gaps and leveraging U.S.-based RTRs and material testing capabilities, leveraging the preliminary evaluation and qualification of selected RTRs to provide a generic as well as specific-case solution paths forward, ensuring adherence to stringent regulatory standards. Furthermore, IRT and radioisotope production utilizing qualified RTRs necessarily includes modeling and simulation to support the design (i.e. neutronics, thermal, and structural aspects) and manufacturing of irradiation test specimens, vehicles, capsules, apparatuses, and flow loops. In addition, IRT can be improved by applying advanced manufacturing techniques and in-pile sensors and instrumentation, as discussed in this study.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

SEC ‐ SAXS / MC Ensemble Structural Studies of the Microtubule Binding Protein Cdt1 Show Monomeric, Folded‐Over Conformations

ABSTRACT Cdt1 is a mixed folded protein critical for DNA replication licensing and it also has a “moonlighting” role at the kinetochore via direct binding to microtubules and the Ndc80 complex. However, it is unknown how the structure and conformations of Cdt1 could allow it to participate in these multiple, unique sets of protein complexes. While robust methods exist to study entirely folded or unfolded proteins, structure–function studies of combined, mixed folded/disordered proteins remain challenging. In this work, we employ orthogonal biophysical and computational techniques to provide structural characterization of mitosis‐competent human Cdt1. Thermal stability analyses shows that both folded winged helix domains1 are unstable. CD and NMR show that the N‐terminal and linker regions are intrinsically disordered. DLS shows that Cdt1 is monomeric and polydisperse, while SEC‐MALS confirms that it is monomeric at high concentrations, but without any apparent inter‐molecular self‐association. SEC‐SAXS enabled computational modeling of the protein structures. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble of structures. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with SAXS. The best‐fit models have the N‐terminal and linker disordered regions extended into the solution and the two folded domains close to each other in apparent “folded over” conformations. We hypothesize the best‐fit Cdt1 conformations could be consistent with a function as a scaffold protein that may be sterically blocked without binding partners. Our study also provides a template for combining experimental and computational techniques to study mixed‐folded proteins.

Cell Biology↗

DOE OSTI2026

Dynamics and Structure of Molten Neodymium Titanate

Binary rare earth titanates can be vitrified using levitation melt quenching, and their glasses are promising for optical applications. To better understand their thermophysical properties and dynamics, we have used molecular dynamics (MD) and empirical potential structure refinement (EPSR) to simulate molten neodymium titanate, 83TiO 2 –17Nd 2 O 3 . The models are compared with high-energy synchrotron X-ray diffraction of the melt structure over 1060–1960 K and thermophysical property measurements of electrostatically levitated droplets over 1500–2200 K. As temperature increases, the network periodicity increases and the correlation length decreases, both in monotonic trends that suggest continuous structural evolution through the melt and supercooled liquid regimes. At 1900 K, the mean Ti–O and Nd–O coordination numbers are 5.8(5) and 6.7(5), compared to the glass, 5.72(6) and 7.70(26). The equilibrium melting point is measured as 1860(20) K, over 100 K higher than previous estimates. Viscosity data from MD are in good agreement with experimental measurements. The dynamic propensity of Nd is similar to that of the network-forming Ti, suggesting that Nd does not participate as a conventional modifier. The viscosity of this fragile liquid is likely controlled by the breaking of cation–oxygen bonds and rearrangements of Ti–O polyhedra.

molecular dynamics↗

DOE OSTI2025

Theory and simulations of cross-beam energy transfer between speckled laser beams

In this paper, we introduce a realistic modeling of laser beams smoothed by random phase plates to investigate cross-beam energy transfer (CBET). We compute the total field of the smoothed laser beams, which allows us to perform accurate simulations and to build a model accounting for the realistic structure of the speckles. This lets us confirm the results already discussed in a previous work given by Oudin et al. [Phys. Plasmas 29, 112112 (2022)]. When CBET is induced by a plasma flow, plane wave models can predict the exchange between smoothed laser beams. By contrast, when the exchange is caused by a wavelength shift between the laser fields of each beam, plane wave models overestimate the energy transfer, even for strongly Landau-damped ion acoustic waves. We also show that the laser angular spread, which results from its focusing, affects the resonance between the ponderomotive force induced by the laser fields and the ion acoustic wave. It increases the resonance width, which weakly depends on the Landau damping rate when there is a wavelength shift and no flow. In addition, the power transfer obtained with or without a phase plate is essentially the same in the perturbative regime and for small crossing angles.

Laser plasma interactions↗

DOE OSTI2024

Development and Experimental Validation of a Heat Transfer Model for Spilled Molten Salt Pools

A spill of radionuclide-bearing molten salt is one of the major postulated events that needs to be analyzed for liquid fluorine salt-cooled high-temperature reactor (FHR) or molten salt reactor licensing purposes. In this postulated event, radioactive source term materials (RSTMs) in the molten salt are discharged from the reactor vessel to the reactor building. The release of RSTMs from the spilled salt pool to the gas space in the reactor building is expected to be controlled by the cooling behavior of the spilled salt, including the growth and shrinkage of the solid crust on the surface of the spilled salt pool. This paper presents a simulation model for spilled salt pool heat transfer and validation efforts. The validation data come from two molten salt spill tests that were performed recently: the PELE2 test by the Rapid Experimental Laboratory of Kairos Power LLC (KP) and the Argonne salt cooling test conducted by Argonne National Laboratory. The former was a large-scale test involving kilograms of molten spilled FLiNaK salt, and the latter was a relatively smaller-scale test targeting various processes associated with a salt spill event. Both tests generated valuable data sets that can be used to assess salt cooling and validate evaluation models. This paper provides a new one-dimensional model that can simulate the cooling process of a spilled salt pool as well as the thermal responses of heat structures, such as the stainless steel liner and the concrete below the salt. The model has been implemented as part of KP-SAM code, which is a branch of the systems code SAM specific to KP FHR. In conclusion, the simulation results of the model are compared with the data of the PELE2 and Argonne tests, and reasonable agreements are observed between the model and test data.

heat transfer model↗

DOE OSTI2025

SOHIP Abel Transform and Onion Peeling Model Module

This software provides tools for analyzing and modeling physical systems using mathematical transforms and layered models. It includes (1) functions for performing the Abel transform, which is used to relate measurements of bending angles to properties such as refractive index and radius in a medium. The code can compute bending angles from input profiles and also reconstruct these profiles from observed data; (2) the functions for modeling systems with multiple layers using an onion-peeling approach, allowing users to simulate and analyze the behavior of layered materials or structures. These capabilities are useful for researchers and engineers working in fields such as optics, atmospheric science, and materials analysis, enabling them to interpret and model data from experiments or simulations relates to refraction in spherical symmetric medium.

Xu, Shuang [Lawrence Livermore National Laboratory↗

DOE OSTI2025

Feasibility of an Accelerometer-Based Structural Health Monitoring System for the LANL Blast Tube

A modeling- and simulation-based study was conducted on the feasibility of implementing an accelerometer-based SHM system on the Los Alamos National Laboratory blast tube. A blast tube experiment was modeled using the Abaqus explicit finite element solver. A custom user subroutine was written to apply test-like pressure loading to the inside surface of the blast tube. The subroutine applies analytically defined pressure loads derived from tracer output taken from a Compressible Flow Computational Fluid Dynamics Solver model of the blast tube. Five unique versions of the model were created: an undamaged reference model at 65°F was used as the baseline and compared to equivalent models at 10°F and 100°F. These three models were compared to models with small damage at the reference temperature. The two types of damage considered were a radial (circumferential) crack in the main tube body and a longitudinal crack in the supports. Acceleration outputs were extracted from accelerometer bodies included in the model and were post processed using a variety of standard SHM techniques. Different potential features signaling failure were extracted and compared using statistical methods in the time and frequency domains. A method was identified that clearly shows that differences in structural response resulting from the modeled damage can be differentiated from the structural response resulting from changing environmental conditions. However, the amount of damage applied to create observable differences in the accelerometer data was so large that simpler methods of damage detection would be more cost effective in locating damage.

42 ENGINEERING↗

DOE OSTI2024

The Role of Unit-Cell Topology in Modulating the Compaction Response of Additively Manufactured Cellular Materials using Simulations and Validation Experiments

Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress–strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress–strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress–strain response.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The role of unit cell topology in modulating the compaction response of additively manufactured cellular materials using simulations and validation experiments

36 MATERIALS SCIENCE↗

DOE OSTI2025

Flux-Closure Domain Structures in Ferroelectric K 0.5 Na 0.5 NbO 3 Thin Films

Topological domain structures in ferroelectric materials have garnered increasing attention due to their intriguing physical properties and promising applications. While most existing topological structures in ferroelectric perovskite oxides originate from tetragonal or rhombohedral bulk phases, much less is understood about their counterparts in orthorhombic ferroelectrics. Here, in this work, we employ ferroelectric K 0.5 Na 0.5 NbO 3 (KNN) thin films as a model system and leverage phase-field simulations to theoretically predict the static structures and dynamic behaviors of three types of flux-closure domain configurations: in-plane (Type-I), out-of-plane (Type-II), and superdomain (Type-III) flux-closure structures. We systematically investigate the effects of finite size, misfit strains, and electrical boundary conditions on the formation and switching of these topological structures. For the Type-I structure, size reduction or small misfit strain facilitates a transition of the flux-closure pattern to polar vortices. Type-II structures emerge under open-circuit electrical boundary conditions of the film, forming at the junctions of specific domain walls with the film surface or the film–substrate interface. The formation mechanisms of these two flux-closure structures are rationalized from an energy perspective. We demonstrated switching capabilities of Type-II and Type-III structures by obtaining polarization–electric field hysteresis loops. Our simulations also reveal a reversible electric-field-induced transition between the orthorhombic and rhombohedral ferroelectric phases with a checkerboard domain pattern, during which the integrity of the flux-closure structure is preserved. These findings provide theoretical insights and practical guidance for identifying and manipulating topological structures in low-symmetry ferroelectrics, paving the way for developing energy-efficient microelectronic devices based on topological structures.

P-E loop↗

DOE OSTI2024

Evaluating Large‐Storm Dominance in High‐Resolution GCMs and Observations Across the Western Contiguous United States

Abstract Extreme precipitation events are projected to increase in frequency across much of the land‐surface as the global climate warms, but such projections have typically relied on coarse‐resolution (100–250 km) general circulation models (GCMs). The ensemble of HighResMIP GCMs presents an opportunity to evaluate how a more finely resolved atmosphere and land‐surface might enhance the fidelity of the simulated contribution of large‐magnitude storms to total precipitation, particularly across topographically complex terrain. Here, the simulation of large‐storm dominance, that is, the number of wettest days to reach half of the total annual precipitation, is quantified across the western United States (WUS) using four GCMs within the HighResMIP ensemble and their coarse resolution counterparts. Historical GCM simulations (1950–2014) are evaluated against a baseline generated from station‐observed daily precipitation (4,803 GHCN‐D stations) and from three gridded, observationally based precipitation data sets that are coarsened to match the resolution of the GCMs. All coarse‐resolution simulations produce less large‐storm dominance than in observations across the WUS. For two of the four GCMs, bias in the median large‐storm dominance is reduced in the HighResMIP simulation, decreasing by as much as 62% in the intermountain west region. However, the other GCMs show little change or even an increase (+28%) in bias of median large‐storm dominance across multiple sub‐regions. The spread in differences with resolution amongst GCMs suggests that, in addition to resolution, model structure and parameterization of precipitation generating processes also contribute to bias in simulated large‐storm dominance.

Environmental Sciences & Ecology↗

DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Data-driven global ocean modeling for seasonal to decadal prediction

Accurate modeling of ocean dynamics is crucial for enhancing our understanding of complex ocean circulation processes, predicting climate variability, and tackling challenges posed by climate change. Although great efforts have been made to improve traditional numerical models, predicting global ocean variability over multiyear scales remains challenging. Here, we propose ORCA-DL (Oceanic Reliable foreCAst via Deep Learning), a data-driven three-dimensional ocean model for seasonal to decadal prediction of global ocean dynamics. ORCA-DL accurately simulates the three-dimensional structure of global ocean dynamics with high physical consistency and outperforms state-of-the-art numerical models in capturing extreme events, including El Niño–Southern Oscillation and upper ocean heat waves. Moreover, ORCA-DL stably emulates ocean dynamics at decadal timescales, demonstrating its potential even for skillful decadal predictions and climate projections. Our results demonstrate the high potential of data-driven models for providing efficient and accurate global ocean modeling and prediction.

Science & Technology - Other Topics↗

DOE OSTI2024

Effect of Part Size, Displacement Rate, and Aging on Compressive Properties of Elastomeric Parts of Different Unit Cell Topologies Formed by Vat Photopolymerization Additive Manufacturing

Due to its ability to achieve geometric complexity at high resolution and low length scales, additive manufacturing (AM) has increasingly been used for fabricating cellular structures (e.g., foams and lattices) for a variety of applications. Specifically, elastomeric cellular structures offer tunability of compliance as well as energy absorption and dissipation characteristics. However, there are limited data available on compression properties for printed elastomeric cellular structures of different designs and testing parameters. In this work, the authors evaluate how unit cell topology, part size, the rate of compression, and aging affect the compressive response of polyurethane-based simple cubic, body-centered, and gyroid structures formed by vat photopolymerization AM. Finite element simulations incorporating hyperelastic and viscoelastic models were used to describe the data, and the simulated results compared well with the experimental data. Of the designs tested, only the parts with the body-centered unit cell exhibited differences in stress–strain responses at different part sizes. Of the compression rates tested, the highest displacement rate (1000 mm/min) often caused stiffer compressive behavior, indicating deviation from the quasi-static assumption and approaching the intermediate rate response. The cellular structures did not change in compression properties across five weeks of aging time, which is desirable for cushioning applications. This work advances knowledge on the structure–property relationships of printed elastomeric cellular materials, which will enable more predictable compressive properties that can be traced to specific unit cell designs.

36 MATERIALS SCIENCE↗